MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples

  1. Chen Chen
  2. Jizhou Li
  3. Lin Di
  4. Qiuyu Jing
  5. Pengcheng Du
  6. Chuan Song
  7. Jiarui Li
  8. Qiong Li
  9. Yunlong Cao
  10. X. Sunney Xie
  11. Angela R. Wu
  12. Hui Zeng
  13. Yanyi Huang
  14. Jianbin Wang

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Abstract

The novel coronavirus disease 2019 (COVID-19) pandemic poses a serious public health risk. Analyzing the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from clinical samples is crucial for the understanding of viral spread and viral evolution, as well as for vaccine development. Existing sample preparation methods for viral genome sequencing are demanding on user technique and time, and thus not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance on viral genomes. We have developed M etagenom I c R N A E n R ichment V ir A l sequencing (MINERVA), a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. This approach uses direct tagmentation of RNA/DNA hybrids using Tn5 transposase to greatly simplify the sequencing library construction process, while subsequent targeted enrichment can generate viral genomes with high sensitivity, coverage, and depth. We demonstrate the utility of MINERVA on pharyngeal, sputum and stool samples collected from COVID-19 patients, successfully obtaining both whole metatranscriptomes and complete high-depth high-coverage SARS-CoV-2 genomes from these clinical samples, with high yield and robustness. MINERVA is compatible with clinical nucleic extracts containing carrier RNA. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate monitoring of viral genetic variations during outbreaks, both current and future.

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    SciScore for 10.1101/2020.04.25.060947: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    bioRxiv Online Publication ( 2020) . doi:10.1101/2020.03.16.993584 10 . Di , L . et al.
    bioRxiv
    suggested: (bioRxiv, SCR_003933)
    Clean data was aligned to GRCm38 genome and known transcript annotation using Tophat2 v2.1.1 .
    Tophat2
    suggested: None
    Ribosome-removed aligned reads were proceeded to calculate FPKM by Cufflinks v2.2.1 and gene body coverage by RSeQC v.2.6.4 .
    Cufflinks
    suggested: (Cufflinks, SCR_014597)
          <div style="margin-bottom:8px">
        <div><b>RSeQC</b></div>
        <div>suggested: (RSeQC, <a href="https://scicrunch.org/resources/Any/search?q=SCR_005275">SCR_005275</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data processing For metagenomic RNA-seq data , raw reads were quality controlled using BBmap ( version 38.68 ) and mapped to the human genome reference ( GRCh38 ) using STAR ( version 2.6.1d ) with default parameters .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>BBmap</b></div>
        <div>suggested: (BBmap, <a href="https://scicrunch.org/resources/Any/search?q=SCR_016965">SCR_016965</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>STAR</b></div>
        <div>suggested: (STAR, <a href="https://scicrunch.org/resources/Any/search?q=SCR_015899">SCR_015899</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All unmapped reads were collected using samtools ( version 1.3 ) for microbial taxonomy assignment by Centrifuge ( version 1.0.4) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>samtools</b></div>
        <div>suggested: (SAMTOOLS, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002105">SCR_002105</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Custom reference was built from all complete bacterial , viral and any assembled fungal genomes downloaded from NCBI RefSeq database ( viral and fungal genomes were downloaded on February 4th , 2020 , and bacterial genomes were downloaded on November 14th , 2018) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>RefSeq</b></div>
        <div>suggested: (RefSeq, <a href="https://scicrunch.org/resources/Any/search?q=SCR_003496">SCR_003496</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For SARS-CoV-2 genome analysis, raw reads were trimmed to remove sequencing adaptors and low-quality bases with Cutadapt v1.15.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Cutadapt</b></div>
        <div>suggested: (cutadapt, <a href="https://scicrunch.org/resources/Any/search?q=SCR_011841">SCR_011841</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then we removed duplicates from the primary alignment with Picard Tools v2.17.6.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Picard</b></div>
        <div>suggested: (Picard, <a href="https://scicrunch.org/resources/Any/search?q=SCR_006525">SCR_006525</a>)</div>
      </div>
    </td></tr></table>

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

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  2. preLights

    Excerpt

    Learning from the past and preparing for the future: Development of a swift and easy RNA sequencing technique on rapidly evolving viral strains

  3. Version published to 10.1101/2020.04.25.060947 on bioRxiv